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Apple

# Staff ML Engineer - Ads ML Infrastructure

New York City, United States of America Senior individual contributor IT & Infrastructure 

Listed on Apple’s official careers site. Posted July 6, 2026. Check that it is still open and apply there.
[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200670904/staff-ml-engineer-ads-ml-infrastructure)

[OpenNash Jobs](https://jobs.opennash.com/) / [Apple](https://jobs.opennash.com/companies/apple/) / Staff ML Engineer - Ads ML Infrastructure

## Job description

At Apple, we work every day to create products that enrich people’s lives. Our Ad Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads, App Store, and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.

The Machine Learning Platform team’s mission is to empower Ad Platforms teams to build and scale the innovative ML systems that deliver highly optimized advertising content to consumers. Are you a results-oriented and versatile engineer who can excel in an Agile environment? You will work closely with engineers and data scientists to design, develop, and build world-class platform capabilities that will enable Ad Platforms teams to improve and scale our ML features, models, and applications.

## At a glance
- Posted by the employer: Jul 6, 2026
- First seen by OpenNash: Jul 10, 2026
- Last checked: Oct 18, 2026
- Listed for: 104 days
- Location: New York City, United States of America[Apply on Apple’s careers site →](https://jobs.apple.com/en-us/details/200670904/staff-ml-engineer-ads-ml-infrastructure)

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OpenNash lists jobs from employers’ own careers sites and does not handle applications.
Dates come from the employer where stated; “first seen” and “last checked” are our own observations.

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